:mod:`logging.config` --- Logging configuration
===============================================

.. module:: logging.config
   :synopsis: Configuration of the logging module.

.. moduleauthor:: Vinay Sajip <vinay_sajip@red-dove.com>
.. sectionauthor:: Vinay Sajip <vinay_sajip@red-dove.com>

**Source code:** :source:`Lib/logging/config.py`

.. sidebar:: Important

   This page contains only reference information. For tutorials,
   please see

   * :ref:`Basic Tutorial <logging-basic-tutorial>`
   * :ref:`Advanced Tutorial <logging-advanced-tutorial>`
   * :ref:`Logging Cookbook <logging-cookbook>`

--------------

This section describes the API for configuring the logging module.

.. _logging-config-api:

Configuration functions
^^^^^^^^^^^^^^^^^^^^^^^

The following functions configure the logging module. They are located in the
:mod:`logging.config` module.  Their use is optional --- you can configure the
logging module using these functions or by making calls to the main API (defined
in :mod:`logging` itself) and defining handlers which are declared either in
:mod:`logging` or :mod:`logging.handlers`.

.. function:: dictConfig(config)

   Takes the logging configuration from a dictionary.  The contents of
   this dictionary are described in :ref:`logging-config-dictschema`
   below.

   If an error is encountered during configuration, this function will
   raise a :exc:`ValueError`, :exc:`TypeError`, :exc:`AttributeError`
   or :exc:`ImportError` with a suitably descriptive message.  The
   following is a (possibly incomplete) list of conditions which will
   raise an error:

   * A ``level`` which is not a string or which is a string not
     corresponding to an actual logging level.
   * A ``propagate`` value which is not a boolean.
   * An id which does not have a corresponding destination.
   * A non-existent handler id found during an incremental call.
   * An invalid logger name.
   * Inability to resolve to an internal or external object.

   Parsing is performed by the :class:`DictConfigurator` class, whose
   constructor is passed the dictionary used for configuration, and
   has a :meth:`configure` method.  The :mod:`logging.config` module
   has a callable attribute :attr:`dictConfigClass`
   which is initially set to :class:`DictConfigurator`.
   You can replace the value of :attr:`dictConfigClass` with a
   suitable implementation of your own.

   :func:`dictConfig` calls :attr:`dictConfigClass` passing
   the specified dictionary, and then calls the :meth:`configure` method on
   the returned object to put the configuration into effect::

         def dictConfig(config):
             dictConfigClass(config).configure()

   For example, a subclass of :class:`DictConfigurator` could call
   ``DictConfigurator.__init__()`` in its own :meth:`__init__()`, then
   set up custom prefixes which would be usable in the subsequent
   :meth:`configure` call. :attr:`dictConfigClass` would be bound to
   this new subclass, and then :func:`dictConfig` could be called exactly as
   in the default, uncustomized state.

   .. versionadded:: 3.2

.. function:: fileConfig(fname, defaults=None, disable_existing_loggers=True, encoding=None)

   Reads the logging configuration from a :mod:`configparser`\-format file. The
   format of the file should be as described in
   :ref:`logging-config-fileformat`.
   This function can be called several times from an application, allowing an
   end user to select from various pre-canned configurations (if the developer
   provides a mechanism to present the choices and load the chosen
   configuration).

   It will raise :exc:`FileNotFoundError` if the file
   doesn't exist and :exc:`RuntimeError` if the file is invalid or
   empty.

   :param fname: A filename, or a file-like object, or an instance derived
                 from :class:`~configparser.RawConfigParser`. If a
                 :class:`!RawConfigParser`-derived instance is passed, it is used as
                 is. Otherwise, a :class:`~configparser.ConfigParser` is
                 instantiated, and the configuration read by it from the
                 object passed in ``fname``. If that has a :meth:`readline`
                 method, it is assumed to be a file-like object and read using
                 :meth:`~configparser.ConfigParser.read_file`; otherwise,
                 it is assumed to be a filename and passed to
                 :meth:`~configparser.ConfigParser.read`.


   :param defaults: Defaults to be passed to the :class:`!ConfigParser` can be specified
                    in this argument.

   :param disable_existing_loggers: If specified as ``False``, loggers which
                                    exist when this call is made are left
                                    enabled. The default is ``True`` because this
                                    enables old behaviour in a
                                    backward-compatible way. This behaviour is to
                                    disable any existing non-root loggers unless
                                    they or their ancestors are explicitly named
                                    in the logging configuration.

   :param encoding: The encoding used to open file when *fname* is filename.

   .. versionchanged:: 3.4
      An instance of a subclass of :class:`~configparser.RawConfigParser` is
      now accepted as a value for ``fname``. This facilitates:

      * Use of a configuration file where logging configuration is just part
        of the overall application configuration.
      * Use of a configuration read from a file, and then modified by the using
        application (e.g. based on command-line parameters or other aspects
        of the runtime environment) before being passed to ``fileConfig``.

    .. versionchanged:: 3.10
       Added the *encoding* parameter.

    .. versionchanged:: 3.11.4
       An exception will be thrown if the provided file
       doesn't exist or is invalid or empty.

.. function:: listen(port=DEFAULT_LOGGING_CONFIG_PORT, verify=None)

   Starts up a socket server on the specified port, and listens for new
   configurations. If no port is specified, the module's default
   :const:`DEFAULT_LOGGING_CONFIG_PORT` is used. Logging configurations will be
   sent as a file suitable for processing by :func:`dictConfig` or
   :func:`fileConfig`. Returns a :class:`~threading.Thread` instance on which
   you can call :meth:`~threading.Thread.start` to start the server, and which
   you can :meth:`~threading.Thread.join` when appropriate. To stop the server,
   call :func:`stopListening`.

   The ``verify`` argument, if specified, should be a callable which should
   verify whether bytes received across the socket are valid and should be
   processed. This could be done by encrypting and/or signing what is sent
   across the socket, such that the ``verify`` callable can perform
   signature verification and/or decryption. The ``verify`` callable is called
   with a single argument - the bytes received across the socket - and should
   return the bytes to be processed, or ``None`` to indicate that the bytes should
   be discarded. The returned bytes could be the same as the passed in bytes
   (e.g. when only verification is done), or they could be completely different
   (perhaps if decryption were performed).

   To send a configuration to the socket, read in the configuration file and
   send it to the socket as a sequence of bytes preceded by a four-byte length
   string packed in binary using ``struct.pack('>L', n)``.

   .. _logging-eval-security:

   .. note::

      Because portions of the configuration are passed through
      :func:`eval`, use of this function may open its users to a security risk.
      While the function only binds to a socket on ``localhost``, and so does
      not accept connections from remote machines, there are scenarios where
      untrusted code could be run under the account of the process which calls
      :func:`listen`. Specifically, if the process calling :func:`listen` runs
      on a multi-user machine where users cannot trust each other, then a
      malicious user could arrange to run essentially arbitrary code in a
      victim user's process, simply by connecting to the victim's
      :func:`listen` socket and sending a configuration which runs whatever
      code the attacker wants to have executed in the victim's process. This is
      especially easy to do if the default port is used, but not hard even if a
      different port is used. To avoid the risk of this happening, use the
      ``verify`` argument to :func:`listen` to prevent unrecognised
      configurations from being applied.

   .. versionchanged:: 3.4
      The ``verify`` argument was added.

   .. note::

      If you want to send configurations to the listener which don't
      disable existing loggers, you will need to use a JSON format for
      the configuration, which will use :func:`dictConfig` for configuration.
      This method allows you to specify ``disable_existing_loggers`` as
      ``False`` in the configuration you send.


.. function:: stopListening()

   Stops the listening server which was created with a call to :func:`listen`.
   This is typically called before calling :meth:`join` on the return value from
   :func:`listen`.


Security considerations
^^^^^^^^^^^^^^^^^^^^^^^

The logging configuration functionality tries to offer convenience, and in part this
is done by offering the ability to convert text in configuration files into Python
objects used in logging configuration - for example, as described in
:ref:`logging-config-dict-userdef`. However, these same mechanisms (importing
callables from user-defined modules and calling them with parameters from the
configuration) could be used to invoke any code you like, and for this reason you
should treat configuration files from untrusted sources with *extreme caution* and
satisfy yourself that nothing bad can happen if you load them, before actually loading
them.


.. _logging-config-dictschema:

Configuration dictionary schema
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^

Describing a logging configuration requires listing the various
objects to create and the connections between them; for example, you
may create a handler named 'console' and then say that the logger
named 'startup' will send its messages to the 'console' handler.
These objects aren't limited to those provided by the :mod:`logging`
module because you might write your own formatter or handler class.
The parameters to these classes may also need to include external
objects such as ``sys.stderr``.  The syntax for describing these
objects and connections is defined in :ref:`logging-config-dict-connections`
below.

Dictionary Schema Details
"""""""""""""""""""""""""

The dictionary passed to :func:`dictConfig` must contain the following
keys:

* *version* - to be set to an integer value representing the schema
  version.  The only valid value at present is 1, but having this key
  allows the schema to evolve while still preserving backwards
  compatibility.

All other keys are optional, but if present they will be interpreted
as described below.  In all cases below where a 'configuring dict' is
mentioned, it will be checked for the special ``'()'`` key to see if a
custom instantiation is required.  If so, the mechanism described in
:ref:`logging-config-dict-userdef` below is used to create an instance;
otherwise, the context is used to determine what to instantiate.

.. _logging-config-dictschema-formatters:

* *formatters* - the corresponding value will be a dict in which each
  key is a formatter id and each value is a dict describing how to
  configure the corresponding :class:`~logging.Formatter` instance.

  The configuring dict is searched for the following optional keys
  which correspond to the arguments passed to create a
  :class:`~logging.Formatter` object:

  * ``format``
  * ``datefmt``
  * ``style``
  * ``validate`` (since version >=3.8)

  An optional ``class`` key indicates the name of the formatter's
  class (as a dotted module and class name).  The instantiation
  arguments are as for :class:`~logging.Formatter`, thus this key is
  most useful for instantiating a customised subclass of
  :class:`~logging.Formatter`.  For example, the alternative class
  might present exception tracebacks in an expanded or condensed
  format.  If your formatter requires different or extra configuration
  keys, you should use :ref:`logging-config-dict-userdef`.

* *filters* - the corresponding value will be a dict in which each key
  is a filter id and each value is a dict describing how to configure
  the corresponding Filter instance.

  The configuring dict is searched for the key ``name`` (defaulting to the
  empty string) and this is used to construct a :class:`logging.Filter`
  instance.

* *handlers* - the corresponding value will be a dict in which each
  key is a handler id and each value is a dict describing how to
  configure the corresponding Handler instance.

  The configuring dict is searched for the following keys:

  * ``class`` (mandatory).  This is the fully qualified name of the
    handler class.

  * ``level`` (optional).  The level of the handler.

  * ``formatter`` (optional).  The id of the formatter for this
    handler.

  * ``filters`` (optional).  A list of ids of the filters for this
    handler.

    .. versionchanged:: 3.11
       ``filters`` can take filter instances in addition to ids.

  All *other* keys are passed through as keyword arguments to the
  handler's constructor.  For example, given the snippet:

  .. code-block:: yaml

      handlers:
        console:
          class : logging.StreamHandler
          formatter: brief
          level   : INFO
          filters: [allow_foo]
          stream  : ext://sys.stdout
        file:
          class : logging.handlers.RotatingFileHandler
          formatter: precise
          filename: logconfig.log
          maxBytes: 1024
          backupCount: 3

  the handler with id ``console`` is instantiated as a
  :class:`logging.StreamHandler`, using ``sys.stdout`` as the underlying
  stream.  The handler with id ``file`` is instantiated as a
  :class:`logging.handlers.RotatingFileHandler` with the keyword arguments
  ``filename='logconfig.log', maxBytes=1024, backupCount=3``.

* *loggers* - the corresponding value will be a dict in which each key
  is a logger name and each value is a dict describing how to
  configure the corresponding Logger instance.

  The configuring dict is searched for the following keys:

  * ``level`` (optional).  The level of the logger.

  * ``propagate`` (optional).  The propagation setting of the logger.

  * ``filters`` (optional).  A list of ids of the filters for this
    logger.

    .. versionchanged:: 3.11
       ``filters`` can take filter instances in addition to ids.

  * ``handlers`` (optional).  A list of ids of the handlers for this
    logger.

  The specified loggers will be configured according to the level,
  propagation, filters and handlers specified.

* *root* - this will be the configuration for the root logger.
  Processing of the configuration will be as for any logger, except
  that the ``propagate`` setting will not be applicable.

* *incremental* - whether the configuration is to be interpreted as
  incremental to the existing configuration.  This value defaults to
  ``False``, which means that the specified configuration replaces the
  existing configuration with the same semantics as used by the
  existing :func:`fileConfig` API.

  If the specified value is ``True``, the configuration is processed
  as described in the section on :ref:`logging-config-dict-incremental`.

* *disable_existing_loggers* - whether any existing non-root loggers are
  to be disabled. This setting mirrors the parameter of the same name in
  :func:`fileConfig`. If absent, this parameter defaults to ``True``.
  This value is ignored if *incremental* is ``True``.

.. _logging-config-dict-incremental:

Incremental Configuration
"""""""""""""""""""""""""

It is difficult to provide complete flexibility for incremental
configuration.  For example, because objects such as filters
and formatters are anonymous, once a configuration is set up, it is
not possible to refer to such anonymous objects when augmenting a
configuration.

Furthermore, there is not a compelling case for arbitrarily altering
the object graph of loggers, handlers, filters, formatters at
run-time, once a configuration is set up; the verbosity of loggers and
handlers can be controlled just by setting levels (and, in the case of
loggers, propagation flags).  Changing the object graph arbitrarily in
a safe way is problematic in a multi-threaded environment; while not
impossible, the benefits are not worth the complexity it adds to the
implementation.

Thus, when the ``incremental`` key of a configuration dict is present
and is ``True``, the system will completely ignore any ``formatters`` and
``filters`` entries, and process only the ``level``
settings in the ``handlers`` entries, and the ``level`` and
``propagate`` settings in the ``loggers`` and ``root`` entries.

Using a value in the configuration dict lets configurations to be sent
over the wire as pickled dicts to a socket listener. Thus, the logging
verbosity of a long-running application can be altered over time with
no need to stop and restart the application.

.. _logging-config-dict-connections:

Object connections
""""""""""""""""""

The schema describes a set of logging objects - loggers,
handlers, formatters, filters - which are connected to each other in
an object graph.  Thus, the schema needs to represent connections
between the objects.  For example, say that, once configured, a
particular logger has attached to it a particular handler.  For the
purposes of this discussion, we can say that the logger represents the
source, and the handler the destination, of a connection between the
two.  Of course in the configured objects this is represented by the
logger holding a reference to the handler.  In the configuration dict,
this is done by giving each destination object an id which identifies
it unambiguously, and then using the id in the source object's
configuration to indicate that a connection exists between the source
and the destination object with that id.

So, for example, consider the following YAML snippet:

.. code-block:: yaml

    formatters:
      brief:
        # configuration for formatter with id 'brief' goes here
      precise:
        # configuration for formatter with id 'precise' goes here
    handlers:
      h1: #This is an id
       # configuration of handler with id 'h1' goes here
       formatter: brief
      h2: #This is another id
       # configuration of handler with id 'h2' goes here
       formatter: precise
    loggers:
      foo.bar.baz:
        # other configuration for logger 'foo.bar.baz'
        handlers: [h1, h2]

(Note: YAML used here because it's a little more readable than the
equivalent Python source form for the dictionary.)

The ids for loggers are the logger names which would be used
programmatically to obtain a reference to those loggers, e.g.
``foo.bar.baz``.  The ids for Formatters and Filters can be any string
value (such as ``brief``, ``precise`` above) and they are transient,
in that they are only meaningful for processing the configuration
dictionary and used to determine connections between objects, and are
not persisted anywhere when the configuration call is complete.

The above snippet indicates that logger named ``foo.bar.baz`` should
have two handlers attached to it, which are described by the handler
ids ``h1`` and ``h2``. The formatter for ``h1`` is that described by id
``brief``, and the formatter for ``h2`` is that described by id
``precise``.


.. _logging-config-dict-userdef:

User-defined objects
""""""""""""""""""""

The schema supports user-defined objects for handlers, filters and
formatters.  (Loggers do not need to have different types for
different instances, so there is no support in this configuration
schema for user-defined logger classes.)

Objects to be configured are described by dictionaries
which detail their configuration.  In some places, the logging system
will be able to infer from the context how an object is to be
instantiated, but when a user-defined object is to be instantiated,
the system will not know how to do this.  In order to provide complete
flexibility for user-defined object instantiation, the user needs
to provide a 'factory' - a callable which is called with a
configuration dictionary and which returns the instantiated object.
This is signalled by an absolute import path to the factory being
made available under the special key ``'()'``.  Here's a concrete
example:

.. code-block:: yaml

    formatters:
      brief:
        format: '%(message)s'
      default:
        format: '%(asctime)s %(levelname)-8s %(name)-15s %(message)s'
        datefmt: '%Y-%m-%d %H:%M:%S'
      custom:
          (): my.package.customFormatterFactory
          bar: baz
          spam: 99.9
          answer: 42

The above YAML snippet defines three formatters.  The first, with id
``brief``, is a standard :class:`logging.Formatter` instance with the
specified format string.  The second, with id ``default``, has a
longer format and also defines the time format explicitly, and will
result in a :class:`logging.Formatter` initialized with those two format
strings.  Shown in Python source form, the ``brief`` and ``default``
formatters have configuration sub-dictionaries::

    {
      'format' : '%(message)s'
    }

and::

    {
      'format' : '%(asctime)s %(levelname)-8s %(name)-15s %(message)s',
      'datefmt' : '%Y-%m-%d %H:%M:%S'
    }

respectively, and as these dictionaries do not contain the special key
``'()'``, the instantiation is inferred from the context: as a result,
standard :class:`logging.Formatter` instances are created.  The
configuration sub-dictionary for the third formatter, with id
``custom``, is::

  {
    '()' : 'my.package.customFormatterFactory',
    'bar' : 'baz',
    'spam' : 99.9,
    'answer' : 42
  }

and this contains the special key ``'()'``, which means that
user-defined instantiation is wanted.  In this case, the specified
factory callable will be used. If it is an actual callable it will be
used directly - otherwise, if you specify a string (as in the example)
the actual callable will be located using normal import mechanisms.
The callable will be called with the **remaining** items in the
configuration sub-dictionary as keyword arguments.  In the above
example, the formatter with id ``custom`` will be assumed to be
returned by the call::

    my.package.customFormatterFactory(bar='baz', spam=99.9, answer=42)

.. warning:: The values for keys such as ``bar``, ``spam`` and ``answer`` in
   the above example should not be configuration dictionaries or references such
   as ``cfg://foo`` or ``ext://bar``, because they will not be processed by the
   configuration machinery, but passed to the callable as-is.

The key ``'()'`` has been used as the special key because it is not a
valid keyword parameter name, and so will not clash with the names of
the keyword arguments used in the call.  The ``'()'`` also serves as a
mnemonic that the corresponding value is a callable.

.. versionchanged:: 3.11
   The ``filters`` member of ``handlers`` and ``loggers`` can take
   filter instances in addition to ids.

You can also specify a special key ``'.'`` whose value is a dictionary is a
mapping of attribute names to values. If found, the specified attributes will
be set on the user-defined object before it is returned. Thus, with the
following configuration::

    {
      '()' : 'my.package.customFormatterFactory',
      'bar' : 'baz',
      'spam' : 99.9,
      'answer' : 42,
      '.' {
        'foo': 'bar',
        'baz': 'bozz'
      }
    }

the returned formatter will have attribute ``foo`` set to ``'bar'`` and
attribute ``baz`` set to ``'bozz'``.

.. warning:: The values for attributes such as ``foo`` and ``baz`` in
   the above example should not be configuration dictionaries or references such
   as ``cfg://foo`` or ``ext://bar``, because they will not be processed by the
   configuration machinery, but set as attribute values as-is.


.. _handler-config-dict-order:

Handler configuration order
"""""""""""""""""""""""""""

Handlers are configured in alphabetical order of their keys, and a configured
handler replaces the configuration dictionary in (a working copy of) the
``handlers`` dictionary in the schema. If you use a construct such as
``cfg://handlers.foo``, then initially ``handlers['foo']`` points to the
configuration dictionary for the handler named ``foo``, and later (once that
handler has been configured) it points to the configured handler instance.
Thus, ``cfg://handlers.foo`` could resolve to either a dictionary or a handler
instance. In general, it is wise to name handlers in a way such that dependent
handlers are configured _after_ any handlers they depend on; that allows
something like ``cfg://handlers.foo`` to be used in configuring a handler that
depends on handler ``foo``. If that dependent handler were named ``bar``,
problems would result, because the configuration of ``bar`` would be attempted
before that of ``foo``, and ``foo`` would not yet have been configured.
However, if the dependent handler were named ``foobar``, it would be configured
after ``foo``, with the result that ``cfg://handlers.foo`` would resolve to
configured handler ``foo``, and not its configuration dictionary.


.. _logging-config-dict-externalobj:

Access to external objects
""""""""""""""""""""""""""

There are times where a configuration needs to refer to objects
external to the configuration, for example ``sys.stderr``.  If the
configuration dict is constructed using Python code, this is
straightforward, but a problem arises when the configuration is
provided via a text file (e.g. JSON, YAML).  In a text file, there is
no standard way to distinguish ``sys.stderr`` from the literal string
``'sys.stderr'``.  To facilitate this distinction, the configuration
system looks for certain special prefixes in string values and
treat them specially.  For example, if the literal string
``'ext://sys.stderr'`` is provided as a value in the configuration,
then the ``ext://`` will be stripped off and the remainder of the
value processed using normal import mechanisms.

The handling of such prefixes is done in a way analogous to protocol
handling: there is a generic mechanism to look for prefixes which
match the regular expression ``^(?P<prefix>[a-z]+)://(?P<suffix>.*)$``
whereby, if the ``prefix`` is recognised, the ``suffix`` is processed
in a prefix-dependent manner and the result of the processing replaces
the string value.  If the prefix is not recognised, then the string
value will be left as-is.


.. _logging-config-dict-internalobj:

Access to internal objects
""""""""""""""""""""""""""

As well as external objects, there is sometimes also a need to refer
to objects in the configuration.  This will be done implicitly by the
configuration system for things that it knows about.  For example, the
string value ``'DEBUG'`` for a ``level`` in a logger or handler will
automatically be converted to the value ``logging.DEBUG``, and the
``handlers``, ``filters`` and ``formatter`` entries will take an
object id and resolve to the appropriate destination object.

However, a more generic mechanism is needed for user-defined
objects which are not known to the :mod:`logging` module.  For
example, consider :class:`logging.handlers.MemoryHandler`, which takes
a ``target`` argument which is another handler to delegate to. Since
the system already knows about this class, then in the configuration,
the given ``target`` just needs to be the object id of the relevant
target handler, and the system will resolve to the handler from the
id.  If, however, a user defines a ``my.package.MyHandler`` which has
an ``alternate`` handler, the configuration system would not know that
the ``alternate`` referred to a handler.  To cater for this, a generic
resolution system allows the user to specify:

.. code-block:: yaml

    handlers:
      file:
        # configuration of file handler goes here

      custom:
        (): my.package.MyHandler
        alternate: cfg://handlers.file

The literal string ``'cfg://handlers.file'`` will be resolved in an
analogous way to strings with the ``ext://`` prefix, but looking
in the configuration itself rather than the import namespace.  The
mechanism allows access by dot or by index, in a similar way to
that provided by ``str.format``.  Thus, given the following snippet:

.. code-block:: yaml

    handlers:
      email:
        class: logging.handlers.SMTPHandler
        mailhost: localhost
        fromaddr: my_app@domain.tld
        toaddrs:
          - support_team@domain.tld
          - dev_team@domain.tld
        subject: Houston, we have a problem.

in the configuration, the string ``'cfg://handlers'`` would resolve to
the dict with key ``handlers``, the string ``'cfg://handlers.email``
would resolve to the dict with key ``email`` in the ``handlers`` dict,
and so on.  The string ``'cfg://handlers.email.toaddrs[1]`` would
resolve to ``'dev_team@domain.tld'`` and the string
``'cfg://handlers.email.toaddrs[0]'`` would resolve to the value
``'support_team@domain.tld'``. The ``subject`` value could be accessed
using either ``'cfg://handlers.email.subject'`` or, equivalently,
``'cfg://handlers.email[subject]'``.  The latter form only needs to be
used if the key contains spaces or non-alphanumeric characters.  If an
index value consists only of decimal digits, access will be attempted
using the corresponding integer value, falling back to the string
value if needed.

Given a string ``cfg://handlers.myhandler.mykey.123``, this will
resolve to ``config_dict['handlers']['myhandler']['mykey']['123']``.
If the string is specified as ``cfg://handlers.myhandler.mykey[123]``,
the system will attempt to retrieve the value from
``config_dict['handlers']['myhandler']['mykey'][123]``, and fall back
to ``config_dict['handlers']['myhandler']['mykey']['123']`` if that
fails.


.. _logging-import-resolution:

Import resolution and custom importers
""""""""""""""""""""""""""""""""""""""

Import resolution, by default, uses the builtin :func:`__import__` function
to do its importing. You may want to replace this with your own importing
mechanism: if so, you can replace the :attr:`importer` attribute of the
:class:`DictConfigurator` or its superclass, the
:class:`BaseConfigurator` class. However, you need to be
careful because of the way functions are accessed from classes via
descriptors. If you are using a Python callable to do your imports, and you
want to define it at class level rather than instance level, you need to wrap
it with :func:`staticmethod`. For example::

   from importlib import import_module
   from logging.config import BaseConfigurator

   BaseConfigurator.importer = staticmethod(import_module)

You don't need to wrap with :func:`staticmethod` if you're setting the import
callable on a configurator *instance*.


.. _logging-config-fileformat:

Configuration file format
^^^^^^^^^^^^^^^^^^^^^^^^^

The configuration file format understood by :func:`fileConfig` is based on
:mod:`configparser` functionality. The file must contain sections called
``[loggers]``, ``[handlers]`` and ``[formatters]`` which identify by name the
entities of each type which are defined in the file. For each such entity, there
is a separate section which identifies how that entity is configured.  Thus, for
a logger named ``log01`` in the ``[loggers]`` section, the relevant
configuration details are held in a section ``[logger_log01]``. Similarly, a
handler called ``hand01`` in the ``[handlers]`` section will have its
configuration held in a section called ``[handler_hand01]``, while a formatter
called ``form01`` in the ``[formatters]`` section will have its configuration
specified in a section called ``[formatter_form01]``. The root logger
configuration must be specified in a section called ``[logger_root]``.

.. note::

   The :func:`fileConfig` API is older than the :func:`dictConfig` API and does
   not provide functionality to cover certain aspects of logging. For example,
   you cannot configure :class:`~logging.Filter` objects, which provide for
   filtering of messages beyond simple integer levels, using :func:`fileConfig`.
   If you need to have instances of :class:`~logging.Filter` in your logging
   configuration, you will need to use :func:`dictConfig`. Note that future
   enhancements to configuration functionality will be added to
   :func:`dictConfig`, so it's worth considering transitioning to this newer
   API when it's convenient to do so.

Examples of these sections in the file are given below.

.. code-block:: ini

   [loggers]
   keys=root,log02,log03,log04,log05,log06,log07

   [handlers]
   keys=hand01,hand02,hand03,hand04,hand05,hand06,hand07,hand08,hand09

   [formatters]
   keys=form01,form02,form03,form04,form05,form06,form07,form08,form09

The root logger must specify a level and a list of handlers. An example of a
root logger section is given below.

.. code-block:: ini

   [logger_root]
   level=NOTSET
   handlers=hand01

The ``level`` entry can be one of ``DEBUG, INFO, WARNING, ERROR, CRITICAL`` or
``NOTSET``. For the root logger only, ``NOTSET`` means that all messages will be
logged. Level values are :ref:`evaluated <func-eval>` in the context of the ``logging``
package's namespace.

The ``handlers`` entry is a comma-separated list of handler names, which must
appear in the ``[handlers]`` section. These names must appear in the
``[handlers]`` section and have corresponding sections in the configuration
file.

For loggers other than the root logger, some additional information is required.
This is illustrated by the following example.

.. code-block:: ini

   [logger_parser]
   level=DEBUG
   handlers=hand01
   propagate=1
   qualname=compiler.parser

The ``level`` and ``handlers`` entries are interpreted as for the root logger,
except that if a non-root logger's level is specified as ``NOTSET``, the system
consults loggers higher up the hierarchy to determine the effective level of the
logger. The ``propagate`` entry is set to 1 to indicate that messages must
propagate to handlers higher up the logger hierarchy from this logger, or 0 to
indicate that messages are **not** propagated to handlers up the hierarchy. The
``qualname`` entry is the hierarchical channel name of the logger, that is to
say the name used by the application to get the logger.

Sections which specify handler configuration are exemplified by the following.

.. code-block:: ini

   [handler_hand01]
   class=StreamHandler
   level=NOTSET
   formatter=form01
   args=(sys.stdout,)

The ``class`` entry indicates the handler's class (as determined by :func:`eval`
in the ``logging`` package's namespace). The ``level`` is interpreted as for
loggers, and ``NOTSET`` is taken to mean 'log everything'.

The ``formatter`` entry indicates the key name of the formatter for this
handler. If blank, a default formatter (``logging._defaultFormatter``) is used.
If a name is specified, it must appear in the ``[formatters]`` section and have
a corresponding section in the configuration file.

The ``args`` entry, when :ref:`evaluated <func-eval>` in the context of the ``logging``
package's namespace, is the list of arguments to the constructor for the handler
class. Refer to the constructors for the relevant handlers, or to the examples
below, to see how typical entries are constructed. If not provided, it defaults
to ``()``.

The optional ``kwargs`` entry, when :ref:`evaluated <func-eval>` in the context of the
``logging`` package's namespace, is the keyword argument dict to the constructor
for the handler class. If not provided, it defaults to ``{}``.

.. code-block:: ini

   [handler_hand02]
   class=FileHandler
   level=DEBUG
   formatter=form02
   args=('python.log', 'w')

   [handler_hand03]
   class=handlers.SocketHandler
   level=INFO
   formatter=form03
   args=('localhost', handlers.DEFAULT_TCP_LOGGING_PORT)

   [handler_hand04]
   class=handlers.DatagramHandler
   level=WARN
   formatter=form04
   args=('localhost', handlers.DEFAULT_UDP_LOGGING_PORT)

   [handler_hand05]
   class=handlers.SysLogHandler
   level=ERROR
   formatter=form05
   args=(('localhost', handlers.SYSLOG_UDP_PORT), handlers.SysLogHandler.LOG_USER)

   [handler_hand06]
   class=handlers.NTEventLogHandler
   level=CRITICAL
   formatter=form06
   args=('Python Application', '', 'Application')

   [handler_hand07]
   class=handlers.SMTPHandler
   level=WARN
   formatter=form07
   args=('localhost', 'from@abc', ['user1@abc', 'user2@xyz'], 'Logger Subject')
   kwargs={'timeout': 10.0}

   [handler_hand08]
   class=handlers.MemoryHandler
   level=NOTSET
   formatter=form08
   target=
   args=(10, ERROR)

   [handler_hand09]
   class=handlers.HTTPHandler
   level=NOTSET
   formatter=form09
   args=('localhost:9022', '/log', 'GET')
   kwargs={'secure': True}

Sections which specify formatter configuration are typified by the following.

.. code-block:: ini

   [formatter_form01]
   format=F1 %(asctime)s %(levelname)s %(message)s
   datefmt=
   style=%
   validate=True
   class=logging.Formatter

The arguments for the formatter configuration are the same as the keys
in the dictionary schema :ref:`formatters section
<logging-config-dictschema-formatters>`.

.. note::

   Due to the use of :func:`eval` as described above, there are
   potential security risks which result from using the :func:`listen` to send
   and receive configurations via sockets. The risks are limited to where
   multiple users with no mutual trust run code on the same machine; see the
   :func:`listen` documentation for more information.

.. seealso::

   Module :mod:`logging`
      API reference for the logging module.

   Module :mod:`logging.handlers`
      Useful handlers included with the logging module.
